Research and Reviews : Journal of Computational Biology

The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate.

Blending predictive data mining with metaheuristic optimization has become essential for tackling tough, real-world problems across all kinds of fields.

In an earlier comparative study of machine-learning methods for genomic prediction of wheat grain yield, we reported a counter-intuitive result: automated nested-cross-validation tuning of the Lasso regularization penalty reduced mean predictive ability relative to a fixed, arbitrarily chosen penalty (mean Pearson r falling from 0.408 to 0.349 across four environments), the opposite of the expected effect of hyperparameter tuning.

Genomic selection (GS) predicts complex quantitative traits directly from genome-wide molecular markers, bypassing the need for extensive phenotypic trials and accelerating plant breeding cycles.

Mangrove ecosystems are critical blue carbon habitats that host diverse microbial communities responsible for carbon cycling and long-term storage.

Artificial intelligence is changing healthcare fast. It is making diagnoses accurate, helping doctors get better results, and streamlining how care works. This paper looks at how AI shows up in healthcare right now – where it is already making a difference, what is working, and what is still tricky.